In mobile devices, noise reduction technologies greatly improve the audio quality. To improve the speech intelligibility in noisy environments, the Active Noise Cancellation (ANC) is an attractive proposition for headsets and the ANC does improve audio reproduction in noisy environment to certain extents. The ANC method has less or no benefits, however, when the mobile phone is being used without ANC headsets. Moreover the ANC method is limited in the frequencies that can be cancelled.
However, in noisy environments, it is difficult to cancel all noise components. The ANC methods do not operate on the speech signal in order to make the speech signal more intelligible in the presence of noise.
Speech intelligibility may be improved by boosting formants. A formant boost may be obtained by increasing the resonances matching formants using an appropriate representation. Resonances can then be obtained in a parametric form out of the linear predictive coding (LPC) coefficients. However, it implies the use of polynomial root-finding algorithms, which are computationally expensive. To reduce computational complexity, these resonances may be manipulated through the line spectral pair representation (LSP). Strengthening resonances consists in moving the poles of the autoregressive transfer function closer to the unit circle. Still this solution suffers from an interaction problem, where resonances which are close to each other are difficult to manipulate separately because they interact. It thus requires an iterative method which can be computationally expensive. But even if proceeded with care, strengthening resonances narrows their bandwidth, which results in an artificially-sounding speech.